Identification of novel amides and alkaloids as putative inhibitors of dopamine transporter for schizophrenia using computer-aided virtual screening

Schizophrenia is a complex psychiatric disorder marked by delusions, memory impairments, hallucinations, disorganized behavior, and severe cognitive deficits. Targeting the dopamine transporter (DAT) protein is promising for treating cognitive symptoms, especially in patients resistant to antipsychotic treatments. In this study, phytochemicals from six medicinal plants underwent virtual screening, and molecular dynamics simulation to identify potential agents targeting DAT. Key drug-like properties, safety, and biological activity were evaluated for identified hits. Pharmacokinetic simulation and pharmacophoric analysis were also performed. Among 990 screened phytochemicals, three alkaloids and six amides, predominantly from <i>Piper retrofractum,</i> and one diterpene were identified as potential antischizophrenic agents based on their stronger binding affinities and favorable docking scores compared to the standard (Lumateperone). Amides showed more potential for DAT than alkaloids. The dynamic behavior and stability of the top three amides, namely, Chenoalbicin, Dipiperamide G, and Lyciumamide C, were evaluated using various molecular dynamics analyses. RMSD (Root Mean Square Deviation), RMSF (Root Mean Square Fluctuation), Rg (Radius of Gyration), and SASA (Solvent Accessible Surface Area) analyses demonstrated favorable characteristics for all three ligands. However, binding free energy, cross-correlation, PCA (Principal Component Analysis) and FEL (Free Energy Landscape) analyses indicated that Lyciumamide C exhibited the highest stability and binding affinity in dynamic environments, Pharmacophoric features highlighted the distinct interacting components for the top three amides. Pharmacokinetic simulations revealed significant peak concentrations and sustained levels can be indicated as Lyciumamide C > Chenoalbicin > Dipiperamide G. The higher and more sustained brain concentrations of Lyciumamide C suggest its most promising pharmacokinetic profile for targeting DAT. Overall, our screened metabolites followed drug-ability criteria and require further experimental validation.

Authors

Institutions

Publication Details

Journal
Frontiers in Pharmacology
Published
2025-04-08
DOI
https://doi.org/10.3389/fphar.2025.1509263
Citations
9
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
13.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of novel amides and alkaloids as putative inhibitors of dopamine transporter for schizophrenia using computer-aided virtual screening

Umar Nishan, Hanna Dib, Sheheryar Sheheryar, Muhammad Shehroz et al.
9 citations
Frontiers in Pharmacology
Computational Drug Discovery Methods
13.54
article

Identification of novel amides and alkaloids as putative inhibitors of dopamine transporter for schizophrenia using computer-aided virtual screening

Umar Nishan, Hanna Dib, Sheheryar Sheheryar, Muhammad Shehroz, Mohamed A. O. Abdelfattah, Mohibullah Shah, Muhammad Umer Khan, Iqra Ahmad, Anam Tassawer
article en
9 citations

Abstract

Schizophrenia is a complex psychiatric disorder marked by delusions, memory impairments, hallucinations, disorganized behavior, and severe cognitive deficits. Targeting the dopamine transporter (DAT) protein is promising for treating cognitive symptoms, especially in patients resistant to antipsychotic treatments. In this study, phytochemicals from six medicinal plants underwent virtual screening, and molecular dynamics simulation to identify potential agents targeting DAT. Key drug-like properties, safety, and biological activity were evaluated for identified hits. Pharmacokinetic simulation and pharmacophoric analysis were also performed. Among 990 screened phytochemicals, three alkaloids and six amides, predominantly from <i>Piper retrofractum,</i> and one diterpene were identified as potential antischizophrenic agents based on their stronger binding affinities and favorable docking scores compared to the standard (Lumateperone). Amides showed more potential for DAT than alkaloids. The dynamic behavior and stability of the top three amides, namely, Chenoalbicin, Dipiperamide G, and Lyciumamide C, were evaluated using various molecular dynamics analyses. RMSD (Root Mean Square Deviation), RMSF (Root Mean Square Fluctuation), Rg (Radius of Gyration), and SASA (Solvent Accessible Surface Area) analyses demonstrated favorable characteristics for all three ligands. However, binding free energy, cross-correlation, PCA (Principal Component Analysis) and FEL (Free Energy Landscape) analyses indicated that Lyciumamide C exhibited the highest stability and binding affinity in dynamic environments, Pharmacophoric features highlighted the distinct interacting components for the top three amides. Pharmacokinetic simulations revealed significant peak concentrations and sustained levels can be indicated as Lyciumamide C > Chenoalbicin > Dipiperamide G. The higher and more sustained brain concentrations of Lyciumamide C suggest its most promising pharmacokinetic profile for targeting DAT. Overall, our screened metabolites followed drug-ability criteria and require further experimental validation.

Frontiers in PharmacologyVol. 16
Bahauddin Zakariya University (PK), University of Lahore (PK), Hainan Normal University (CN), Kohat University of Science and Technology (PK), Universidade Federal do Ceará (BR), American University of the Middle East (KW), Kohsar University Murree
Bahauddin Zakariya University
Good health and well-being
Openalex Percentile: Top 1%
Computational Drug Discovery Methods
13.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.